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Article

Five Uses for Data Segmentation

February 19, 2024

by Mac Thompson

Founder/CEO

White Clay

4 minutes

To make your offerings and delivery channels more relevant to members, you must first understand your member data.

Today’s banking environment looks very different to what credit unions were used to 15 or even just five years ago. A look at the past will show interest rates close to 0%, cheap cost of deposits and capital and high demand for loans. Things are different now. The growing cost of deposits and capital, paired with high interest rates and shrinking loan revenues have led to lower profit margins. As a result, credit unions are under pressure to adapt and perform.

With limited time and resources, the best way for credit unions to grow is to look inward and optimize existing assets. Credit unions’ biggest assets are their relationships with their members. These financial institutions are already known for their superior member service and personalization, but what if there’s an opportunity to dig even deeper into existing relationships?

A Mountain of Data

Credit unions sit on a mountain of raw member data; data that is highly variable and does not inherently provide actionable insights. But modern technologies, like machine learning tools and trend analysis algorithms, can help credit unions clean and analyze the raw data to get a clearer view of members’ banking relationships. Clean data can then be reliably divided and grouped into similar segments. Credit unions can apply segmentation to:

Identify who their members are by personal attributes (i.e., age, gender, ethnicity, occupation, income, etc.), defined geographical boundaries (i.e., region, state, ZIP code) and lifestyles (i.e., habits, interests and so on). This will also help determine members’ profitability characteristics (i.e., estimated revenue, profitability and cost), product and service usage and the type of relationship they have with the credit union or other identified FIs (i.e., primary vs. secondary).

Credit unions will then be able to use these insights to design, execute and manage a playbook to optimize behavior for each segment. For example, they could offer temporary discounts or incentives related to hobbies or a move to boost engagement and improve member satisfaction, turning secondary or unengaged relationships into primary ones. (Does a member who just bought a house use their credit card at a lot of home improvement stores? Offer a HELOC.) CUs can also personalize communication based on each member’s geographical location, age, or interests, making them feel seen and understood.
Understand where the majority of their deposits are, and which are most at risk. This is especially important as experts predict historically low deposit growth in 2024. A clear view of where liquidity sits will help credit unions price those accounts correctly and boost revenue. Identifying at-risk deposits will prompt credit unions to work on retaining those accounts, issuing offers specific to them (e.g., higher interest rates, better rewards, or temporary discounts). Offering members great experiences now might also incentivize them to move their secondary deposit relationships—the deposits they might have in other financial institutions or fintechs—over to the credit union.
Discover cross-sell opportunities by spotting members who might benefit from additional products or services, for example a savings account, a new credit card or an auto loan. This will help service reps decide which relationships to prioritize, improving those members’ banking experience, boosting retention rates and driving growth for the institution.
Find out what engagement channels are—and are not—most effective. This can guide credit unions away from shutting down branches frequented by their best members or turning off popular digital channels that drive revenue. On the flip side, it can also help executive teams decide which non-essential channels they can close, saving costs and increasing efficiency.
Drive technology strategy. Knowing what technologies are most popular and effective (e.g., online banking, online account opening or loan origination) can help credit unions decide which fintechs they want to partner with. Every year, we see many new fintech players and offerings emerge, making it increasingly difficult for financial institutions to determine which technologies they should invest in. Segmentation can help provide guidance, driving a technology strategy that best fits your institution’s needs.

2024 is the year credit unions should look inward and focus on expanding their existing member relationships. Cleaning and analyzing the data that they already have and applying segmentation will help organizations understand who their members are, which engagement channels are effective, which products and services work best and where their deposits sit. This new level of insight will help credit unions uncover new opportunities within their existing membership, improving both member satisfaction and shareholder value, and better serving their communities.

Mac Thompson is founder/CEO of White Clay, which provides financial institutions with a single, accurate view of their data to optimize profitability and liquidity, protect shareholder value, and improve relationships. Please visit http://www.whiteclay.com/ for more information.

Five Uses for Data Segmentation

To make your offerings and delivery channels more relevant to members, you must first understand your member data.

A Mountain of Data

Elevate your leadership potential with the latest from CUES

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Five Uses for Data Segmentation

To make your offerings and delivery channels more relevant to members, you must first understand your member data.

A Mountain of Data

Elevate your leadership potential with the latest from CUES

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